# -*- coding: utf-8 -*-

''' Autor: Neuza Figueira - n.º 6036 '''

from insertionSort import InsertionSort
from random import randint
from time import clock
import matplotlib.pyplot as plt

class BucketSort():
        ''' Class to handle Bucket sort implementation and testing.'''
        
        def bucket_sort(self, A):
                '''Python Implementation of Bucket sort.'''
                '''@param A -> List to sort.'''
                insertion = InsertionSort()
                n = len(A)
                B = [[] for x in range(n)]
                
                for x in A:
                        B[x / n].append(x)

                for bucket in B:
                        insertion.insertion_sort(bucket)


                sorted_list = []
                for bucket in B:
                        sorted_list = sorted_list + bucket


                return sorted_list

        
        def testBucketSort(self):
                '''Testing the complexity of Bucket sort.'''
                Z = range(50, 1050, 50)
                T = []
                M = 50
                for n in Z:
                    A = [ randint(0, 100) for k in xrange(n)]
                    tempos = []   
                    for k in range(M):
                        t1 = clock()
                        self.bucket_sort(A)
                        t2 = clock()
                        tempos.append(t2-t1)
                        
                    media = reduce(lambda x, y: x + y, tempos) / len(tempos)
                    var = reduce(lambda x, y: x + (y-media)**2, [0] + tempos) / len(tempos)

                    T.append((n,media, var))

                X = [n for n, media, var in T]
                Y = [media for n, media, var in T]
                ct = 10e6
                Z = [(n**2 / ct) for n, media, var in T]


                plt.grid(True)
                plt.ylabel(u'T(n) - tempo de execução médio em segundos')
                plt.xlabel(u'n - número de elementos')
                plt.plot(X,Y,'rs', label="resultado experimental")
                plt.plot(X, Z, 'b^', label=u"previsão teórica")
                plt.legend()
                plt.show()
                pass
